Saving future lives. A comparison of three discounting models

Area of Science:

• Behavioral Economics
• Decision Theory
• Public Health

Background:

• Intertemporal choice models are crucial for understanding decisions involving future outcomes.
• Saving future lives presents a unique challenge for economic valuation and discounting.
• Existing models like constant discounting may not fully capture real-world preferences.

Purpose of the Study:

• To compare the explanatory power of three intertemporal choice models: constant, proportional, and hyperbolic discounting.
• To assess the suitability of different statistical methods for analyzing multilevel data in this context.
• To determine which discounting model best reflects public choices regarding saving future lives.

Main Methods:

• Data were collected from the general public on choices related to saving future lives.
• Three intertemporal choice models (constant, proportional, hyperbolic discounting) were applied.
• Statistical analyses included ordinary least-squares (OLS) and multilevel modeling due to data structure.

Main Results:

• Proportional discounting models showed significant support compared to constant discounting.
• Hyperbolic discounting models also demonstrated better fit than constant discounting.
• Multilevel analysis was found to be more appropriate and effective than OLS for the collected data.

Conclusions:

• Proportional and hyperbolic discounting models offer superior frameworks for understanding intertemporal choices concerning future life-saving.
• The multilevel structure of public preference data necessitates advanced analytical techniques.
• Findings inform policy and interventions aimed at promoting long-term investments in life-saving initiatives.